This invention relates to electromagnetic signal measuring instrumentation and, more particularly, to EMI measuring devices. Specifically, the invention is directed to a method and apparatus for narrowband signal recognition for EMI measurement using automated EMI measurement instruments, for example, automated open-site EMI measurement instruments.
Test procedures for open-site, radiated emission measurements are often time-consuming and tedious, requiring constant attention to detail. The extant demand for fast product testing turnover has created a clear need to increase productivity of radiated emission testing.
Open-site radiated emission measurements follow the guidelines promulgated by an international committee established for this purpose. The acronym for this committee is CISPR. The measurement studies and recommendations of CISPR are used worldwide as the basis on which to regulate emissions from commercial electronic and electric products Although limits of radiated field strength adopted by different countries may vary, the CISPR measurement guidelines are becoming the general standard.
CISPR guidelines specify that compliance measurements be made outdoors in a natural radio frequency (RF) environment. The transducers used in these measurements are generally broadband, calibrated antennas. Such antennas are varied in height and polarity so that the maximum of any radiating field from equipment under test (EUT) can be found. CISPR recommends distances between antenna and EUT and also requires the EUT to be rotated to find the maximum(s). Additionally, the bandwidths and the type of detection used by the measuring receiver are specified.
To define a test procedure that can be automated, the many complexities of the measurement environment must first be understood. Fortunately, open-site compliance measurements begin at 30 megahertz (MHz), whereas below 30 MHz, there is an abundance of radio signals, many large signals, and many more intermittent transmissions. Above 30 MHz, signals become more localized and predictable, but there can still be a large number and variety of transmissions, as shown in FIG. 1. Many of these signals, such as TV and FM radio transmissions, are the most powerful signals. EMI measurements near these strong fields are challenging. The possibility exists of over-driving the input circuitry of the measuring receiver, resulting in overload and erroneous readings. This problem is compounded when EMI measurements are attempted where there are many strong signals close together, such as in the FM radio band. The effective noise floor of the receiver is raised by the close spacing of the transmissions. This decreases the dynamic range between the limit and the noise floor, such that it becomes difficult to identify emissions. To regain some measurability, the resolution bandwidth of the measuring receiver may have to be lowered to resolve signals adjacent to and between large signals.
Also, unpredictable ambient emissions, such as intermittent transmissions produced by keyed transmission sources, can be mistaken for EUT emissions. Another complicating factor in some locations is the presence of broadband, incoherent noise or coherent, impulsive noise. These signals are produced by nearby vehicle ignition systems, industrial switching circuits, or even power lines swaying in the wind. As a result of all these emission sources, every site on which EMI measurements are made is different and has its own set of complexities that the site operator must deal with in developing a test plan. A site operator must become familiar with the ambient environment and make decisions during the tests based on this familiarity.
There are also complexities to EUT emissions. Usually EUT emissions from various products tested are directional and exhibit large variations in amplitude as the EUT is rotated. A first order approximation of the EUT azimuth variability and pre-positioning is desirable before any identification process begins.
Sometimes emissions are related to the operational state of the EUT. Having control of the EUT to establish these states requires knowledge of operation of the EUT. Also, a number of emission types can be radiated by the EUT. For example, EUT clocks produce narrowband emissions at specific frequencies and harmonics. Clock designs using ceramic resonators instead of crystal control can exhibit frequency jitter or instability. Products containing switching power supplies or generating fast rise-time pulses often produce broadband emissions. In other words, before open-site measurements begin, it is advantageous to learn something about the EUT by scanning with the antenna moved in close, or pre-scanning in a shielded room.
A test procedure based on complete turn-key automation, in which site operator discretion is eliminated, is not possible due to the complexities mentioned above. However, the complexity of CISPR radiated emission testing can be reduced and made less tedious and time-consuming.
One problem of known EMI measurement systems has been difficulty in discriminating between narrowband signals. Typically, this problem arises when measurements are performed to determine both the presence of ambient signals and the emission characteristics of the EUT.
Specifically, as a spectrum analyzer is swept across a frequency range to measure signals, signals appear at various spectral locations. However, due to complexities of both the measurement environment and EUT emissions, the frequency of a signal transmission can vary. Also, the measuring receiver can produce measurement errors. These are problems which either cannot be overcome (e.g., signal transmission uncertainties) or must be otherwise solved (i.e., improving the accuracy and precision of the measuring receiver).
However, digital uncertainties arising from the frequency span and the number of measurements performed during a sweep and the width of the resolving bandpass filter of the measuring receiver also affect the discrimination of narrowband signals, such as two ambient signals or an ambient signal and a suspected EUT emission. Previously, a percentage of the frequency span has been applied as the factor to discriminate between signals, i.e., if one signal is less than or equal to a predetermined percentage of the frequency span from another signal measured at a different time, they are considered to be the same. This technique of signal recognition produces unsatisfactory results, particularly when the frequency span is wide.